Given the recent advances in digital camera technology, users may accumulate digital image collections having hundreds of digital images. As a result, it is becoming increasingly difficult for users to organize their digital image collections such that they can easily and quickly find desired images. One method for assisting a user in finding digital images within his collection is tagging the digital images with keywords such as “Christmas 2004,” “Italy,” “Vacation,” and the like. However, the typical the tagging process is manually intensive. In general, tagging typically occurs after the user has uploaded numerous digital images from his digital camera to his personal computer. Each digital image may then be tagged with one or more keywords by either manually entering the keywords or selecting the keywords from a static list of keywords previously created by the user.
One problem associated with the typical tagging process is that the process becomes prohibitively time consuming for the average user if the user must manually enter the desired keywords. Further, even in the systems that allow the user to select the desired keywords from a static list of keywords, the user may be forced to sort through many keywords that are not particularly relevant to find the desired keywords. In addition, the static list may not contain many relevant keywords. Thus, there remains a need for a system that automates much of the tagging process and that intelligently suggests keywords to the user.